Abstract
We have investigated structural distance metrics for linear genetic programs. Causal connections between changes of the genotype and changes of the phenotype form a necessary condition for analyzing structural differences between genetic programs and for the two objectives of this paper: (i) Distance information between individuals is used to control structural diversity of population individuals actively by a two-level tournament selection. (ii) Variation distance is controlled on the effective code for different genetic operators - including a mutation operator that works closely with the applied distance metric. Numerous experiments have been performed for three benchmark problems.
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Brameier, M., Banzhaf, W. (2002). Explicit Control of Diversity and Effective Variation Distance in Linear Genetic Programming. In: Foster, J.A., Lutton, E., Miller, J., Ryan, C., Tettamanzi, A. (eds) Genetic Programming. EuroGP 2002. Lecture Notes in Computer Science, vol 2278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45984-7_4
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DOI: https://doi.org/10.1007/3-540-45984-7_4
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